Hydrodeoxygenation of guaiacol over molybdenum‐based catalysts: The effect of support and the nature of the active site
Bibliographic record
Abstract
Abstract The hydrodeoxygenation (HDO) of guaiacol has been chosen as a model process for the upgrading of lignin‐derived bio‐oils. Tests were carried out in a batch reactor at 350 °C, 4000 kPa of H2, in the presence of several Mo‐based catalysts prepared by impregnation of ammonium molybdate on SiO2, Al2O3, NaY zeolite, MgO, activated carbon, and graphite. These materials have been characterized by means of: N2 physisorption, XRD, FESEM/EDS, XPS, TPR‐H2, and TPD‐NH3, with the aim of correlating the physical and chemical properties of the prepared samples with the resulting features in the HDO reaction. Mo on activated carbon showed the best performances towards guaiacol demethoxylation, exhibiting complete conversion, 72 % of selectivity to phenol, and 19 % to p‐ and o‐cresol. The high surface area and low acidity of activated carbon allow good dispersion of MoOx which exhibits characteristic fragments with a lamellar shape, able to provide a large active surface with localized acidity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".